Time-dependent kinematic reliability analysis of gear mechanism based on sequential decoupling strategy and saddle-point approximation

•Time-dependent kinematic reliability of gear mechanisms is analyzed.•An efficient TDKR method for gear mechanisms is presented.•Dynamic reliability-based sensitivity is investigated for the parameters’ effects.•The accuracy and efficiency of the proposed method are validated. Accurate and efficient...

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Bibliographic Details
Published in:Reliability engineering & system safety 2022-04, Vol.220, p.108292, Article 108292
Main Authors: Chen, Junhua, Chen, Longmiao, Qian, Linfang, Chen, Guangsong, Zhou, Shijie
Format: Article
Language:English
Subjects:
Approximation
Approximation method
Back propagation networks
Computer programming
Decoupling
Dynamic models
Gear mechanism
Global optimization
Kinematics
Limit states
Mathematical analysis
Monte Carlo simulation
Neural networks
Reliability analysis
Reliability engineering
Saddle points
Saddle-point approximation
Sequence decoupling strategy
Time dependence
Time-dependent kinematic reliability
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Summary:•Time-dependent kinematic reliability of gear mechanisms is analyzed.•An efficient TDKR method for gear mechanisms is presented.•Dynamic reliability-based sensitivity is investigated for the parameters’ effects.•The accuracy and efficiency of the proposed method are validated. Accurate and efficient reliability evaluation is critical to ensure the safety of gear mechanism. This paper aims to develop an effective and practical method for time-dependent kinematic reliability of gear mechanism. Firstly, dynamic model of gear mechanism is established, and a surrogate model of kinematic error is obtained based on BP neural network. After that, we employ a sequential decoupling strategy of efficient global optimization to transform the time-dependent reliability problem into a time-independent one, with which the second-order information of the extreme limit-state function can be then obtained. Finally, the saddle-point approximation method is applied to estimate the time-dependent kinematic reliability of the gear mechanism. The accuracy and efficiency of the proposed method are verified by several engineering problems, and comparisons are made against other existing reliability methods. Results of the engineering cases show that the proposed method can effectively reduce the limit-state function call numbers while reaching the same accuracy as Monte Carlo Simulation.
ISSN:0951-8320
1879-0836
DOI:10.1016/j.ress.2021.108292